Frontend Engineer

Technical Skills:

* Advanced proficiency in Python.

* Extensive experience with LLM frameworks (Hugging Face Transformers, LangChain) and prompt engineering techniques

* Experience with big data processing using Spark for large-scale data analytics

* Version control and experiment tracking using Git and MLflow

* Software Engineering & Development: Advanced proficiency in Python, familiarity with Go or Rust, expertise in microservices, test-driven development, and concurrency processing.

* DevOps & Infrastructure: Experience with Infrastructure as Code (Terraform, CloudFormation), CI/CD pipelines (GitHub Actions, Jenkins), and container orchestration (Kubernetes) with Helm and service mesh implementations.

* LLM Infrastructure & Deployment: Proficiency in LLM serving platforms such as vLLM and FastAPI, model quantization techniques, and vector database management.

* MLOps & Deployment: Utilization of containerization strategies for ML workloads, experience with model serving tools like TorchServe or TF Serving, and automated model retraining.

* Cloud & Infrastructure: Strong grasp of advanced cloud services (AWS, GCP, Azure) and network security for ML systems.

* LLM Project Experience: Expertise in developing chatbots, recommendation systems, translation services, and optimizing LLMs for performance and security.

* General Skills: Python, SQL, knowledge of machine learning frameworks (Hugging Face, TensorFlow, PyTorch), and experience with cloud platforms like AWS or GCP.

* Experience in creating LLD for the provided architecture.

* Experience working in Microservices based architecture

Domain Expertise:

* Strong mathematical foundation in statistics, probability, linear algebra, and optimization

* Deep understanding of ML and LLM development lifecycle, including fine-tuning and evaluation

* Expertise in feature engineering, embedding optimization, and dimensionality reduction

* Advanced knowledge of A/B testing, experimental design, and statistical hypothesis testing

* Experience with RAG systems, vector databases, and semantic search implementation

* Proficiency in LLM optimization techniques including quantization and knowledge distillation

* Understanding of MLOps practices for model deployment and monitoring

Professional Competencies:

* Strong analytical thinking with ability to solve complex ML challenges

* Excellent communication skills for presenting technical findings to diverse audiences

* Experience translating business requirements into data science solutions

* Project management skills for coordinating ML experiments and deployments

* Strong collaboration abilities for working with cross-functional teams

* Dedication to staying current with latest ML research and best practices

Must Have : Microservices LLM, Python, FastAPI, Vector DB(Qdrant, Chromadb, stc), RAG, MLOps & Deployment, Cloud, Agentic AI Framework, Kubernetes, Architecture & Design

Secondary Skills - Data science, ML and NLP